Medibot for Emergency Vehicle

To create a medical robot that would be installed in an ambulance and use IoT to observe and communicate so that the patient might receive care before being brought to the hospital. In the case of a mishap, installing a finger print sensor will enable the hospital emergency room, police station, and the patient’s guardian to be informed of the unfamiliar patient’s bio-data. There are still significant problems with overpopulation and health-related illiteracy in India, and an accident-related mortality happens every minute. To build a clever smart health system, a MediBoT made up of sensors and microcontrollers is intended. It will assess the body’s condition and send information to the IoT

Eco-friendly and facile integrated biological-cum-photo assisted electrooxidation process for degradation of textile wastewater

The present article reports an integrated treatment method viz biodegradation followed by photo-assisted electrooxidation, as a new approach, for the abatement of textile wastewater. In the first stage of the integrated treatment scheme, the chemical oxygen demand (COD) of the real textile effluent was reduced by a biodegradation process using hydrogels of cellulose-degrading Bacillus cereus. The bio-treated effluent was then subjected to the second stage of the integrated scheme viz indirect electrooxidation (InDEO) as well as photo-assisted indirect electro oxidation (P-InDEO) process using Ti/IrO2-RuO2-TiO2 and Ti as electrodes and applying a current density of 20 mA cm-2. The influence of cellulose in InDEO has been reported here, for the first time. UV-Visible light of 280-800 nm has been irradiated toward the anode/electrolyte interface in P-InDEO. The effectiveness of this combined treatment process in textile effluent degradation has been probed by chemical oxygen demand (COD) measurements and 1H - nuclear magnetic resonance spectroscopy (NMR). The obtained results indicate that the biological treatment allows obtaining a 93% of cellulose degradation and 47% of COD removal, increasing the efficiency of the subsequent InDEO by a 33%. In silico molecular docking analysis ascertained that cellulose fibers affect the InDEO process by interacting with the dyes that are responsible of the COD. On the other hand, P-InDEO resulted in both 95% of decolorization and 68% of COD removal, as a result of radical mediators. Free radicals generated during P-InDEO were characterized as oxychloride (OCl) by electron paramagnetic resonance spectroscopy (EPR). This form of coupled approach is especially suggested for the treatment of textile wastewater containing cellulose

Real-time sensor signal capture from a harsh environment

Understanding the baseline underwater acoustic signature of an offshore location is a necessary, early step in formulating an environmental impact assessment of wave energy conversion devices. But in order to even begin this understanding, infrastructure must be deployed to capture raw acoustic signals for an extended period of time. This infrastructure is comprised of at least four distinct components. Firstly, a hydrophone, deployed underwater, which is capable of operating at a high sampling rate: 500,000 16–bit samples per second. Secondly, an analog/digital converter (ADC), to which the hydrophone transmits raw voltages. Thirdly, a communications infrastructure for bridging the gap from the ADC to shore. And finally, an onshore base-station for receiving the signals and presenting them to a remote analytic or simulation infrastructure for further processing. Attempting this signal capture in real-time poses many problems. On a practical level, deploying cabled infrastructure to deliver power and communications to the offshore components may be prohibitively expensive. However, reliance on solar power may result in interruptions to real-time wireless transmission. Additionally, a high sampling rate will require significant base-station memory/storage/processing capabilities as well as potentially high costs of delivery to a remote infrastructure, part of which could be alleviated by realtime signal compression. This paper discusses our attempts at implementing such a system which would reliably acquire real-time data and scale with growing demands